Help programming function using dplyr and the _ versions of commands

[Michael Ash]

The point of the function in the MWE program below is to start with a dataframe with variables z,x1,x2,and y and to generate a new dataframe that is ordered by z and contains z, the first difference of x1, the first difference of x2, and the first difference of y. 

I'm confused by the referencing and dereferencing rules in dplyr, the underscore versions of the basic dplyr functions, e.g., mutate_, and why assignments don't seem to work normally but apparently need I().  

The code below sort of works, but I can't figure out how to name the transformation of the individual x variables (I'm planning to do this with many variables, not just x1 and x2).  The program currently overwrites the previous x variable each time the loop runs. Also, although I use the "~" and as.name() constructions that are recommended by some of the web pages on programming with dplyr, I don't really understand what I'm doing.  I also suspect that although the ~I() construction works, it is considered inelegant compared to what I'm supposed to be doing.

Comments or suggestions welcome. I've been working as best I can from, for example, http://dplyr.tidyverse.org/articles/programming.html

Thank you.

Yours,

Michael

(my.D = data.frame(my.y=runif(10), my.x1=runif(10), my.x2=1:10, my.z=runif(10)))

my.plm  <- function(D,y,x,z) {

    require(dplyr)

    require(lazyeval)

    z  <- as.name(z)

    y  <- as.name(y)

    print(D  <- arrange_(D,z))

    print(summarize_( D,~mean(z),~mean(y) ))

    print(D.fd  <- mutate_(D,

                     z = z,

                     y = ~I(y - lag(y,n=1L))

               )

          )

    for(xvar in x) {

        print(varname  <- paste("x_", xvar, sep=""))

        xvar  <- as.name(xvar)

        print(D.fd  <- mutate_(D.fd,

                           ~I(xvar - lag(xvar,n=1L))

                           )

              )

    }

}

my.plm(D=my.D,y="my.y",x=c("my.x1","my.x2"),z="my.z")

[M. Edward (Ed) Borasky]

I'd go with the almost-released dplyr 0.6.0 out of GitHub and learn the new API. It's quite different from the "_" convention but it's well documented, so unless you're on a deadline maintaining some code I'd move up to the new semantics.

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